Empirical Study on Effect of Silicon Application on Rice Blast Disease and Plant Morphology in Indonesia
Bibliographic record
Abstract
Si fertilizer was never used in rice cultivation by farmers in Indonesia. To evaluate the effect of Si application on blast disease, plant morphologies, and stomata formation on rice plant, a field experiment was conducted in West Java, Indonesia. Two treatments, Si+ (with 1000 kg ha-1 of silica gel) and Si- (without Si application) were set in a randomized complete block design. The results showed that Si application in soil with high available Si 426 mg SiO2 kg-1 significantly reduce leaf (p < 0.01) and neck (p < 0.05) blast disease infection and increased stomata density (p < 0.01). Si- had severer leaf blast infection than Si+ which could reach up to score 4 and 5. Si deposited on the tissue surface acts as a physical barrier by thickening the Si layer in cuticle which could decrease the number of blast lessions on leaf blades by limiting hypa penetration and invasion. Recently there was no report to prove whether Si deposition improves or changes the stomata density. The results confirmed that Si application have the potential of improving rice growth and yield through the increase of resistance to blast infection and increment in stomata density although they did not result in the yield increment in the present study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".